Rapid UAV-based monitoring and discrimination method for drought in summer maize based on chlorophyll content

US12405259B2 · kind B2 · utility

Assignee

• China Institute of Water Resources and Hydropower Research · CN

Inventors

• Wenlong SONG · Sichuan, CN
• Mengyi Li · Beijing, CN
• Changjun Liu · Sichuan, CN
• Pu Zhou · Beijing, CN
• Lang Yu · Beijing, CN
• Yizhu LU · Beijing, CN
• Yun-Wen Liu · Beijing, CN
• Wenjing Lu · Shanghai, CN
• Xiuhua Chen · Beijing, CN
• Long Chen · Beijing, CN

Key dates

• Filing date: Dec 23, 2024
• Grant date: Sep 2, 2025
• Expiry date: Dec 23, 2044

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V20/194
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

A rapid monitoring and discrimination method for drought conditions in summer maize based on chlorophyll content includes: 1) Obtaining multi-spectral imagery through UAV multi-payload low-altitude remote sensing technology and measuring chlorophyll content on the ground. Additionally, calculating vegetation indices including Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and Renormalized Difference Vegetation Index (RENDVI). 2) Selecting vegetation indices and constructing regression equations with measured chlorophyll content during different growth stages. The regression equation with the highest correlation for each growth stage is chosen as the optimal model equation for that particular stage. 3) Using the optimal model equations to retrieve chlorophyll content for each period and determining thresholds for chlorophyll content across different drought levels through calibration. 4) Calculating the required vegetation indices from real-time multi-spectral imagery of the field under test, retrieving chlorophyll content, and comparing it with the established thresholds to assess the real-time drought level.